def __init__(self):
"""
Initializes a new instance of this class.
"""
# Index of this cell in the spatial pooler.
self.index_sp = -1
# Index of this synapse in the temporal pooler.
self.index_tp = -1
# An input element is a cell in case of the source be a column or then a bit in case of the source be a sensor.
self.input_elem = None
# Permanence of this synapse.
self.permanence = MachineState(0.0, MAX_PREVIOUS_STEPS)
# States of this element
self.is_connected = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_predicted = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_falsely_predicted = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_removed = MachineState(False, MAX_PREVIOUS_STEPS)
# Statistics
self.stats_connection_count = 0
self.stats_connection_rate = 0.0
self.stats_predition_count = 0
self.stats_precision_rate = 0.0
# 3D object reference
self.tree3d_initialized = False
self.tree3d_item_np = None
self.tree3d_selected = False
def __init__(self):
"""
Initializes a new instance of this class.
"""
# Index of this cell in the temporal pooler.
self.index = -1
# Position on Z axis
self.z = -1
# List of distal segments of this cell.
self.segments = []
# States of this element
self.is_learning = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_active = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_predicted = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_falsely_predicted = MachineState(False, MAX_PREVIOUS_STEPS)
# Statistics
self.stats_activation_count = 0
self.stats_activation_rate = 0.0
self.stats_predition_count = 0
self.stats_precision_rate = 0.0
# 3D object reference
self.tree3d_initialized = False
self.tree3d_pos = (0, 0, 0)
self.tree3d_item_np = None
self.tree3d_selected = False
def __init__(self, type):
"""
Initializes a new instance of this class.
"""
# Determine if this segment is proximal or distal.
self.type = type
# Index of this segment in the temporal pooler.
self.index_tp = -1
# List of distal synapses of this segment.
self.synapses = []
# States of this element
self.is_active = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_predicted = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_falsely_predicted = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_removed = MachineState(False, MAX_PREVIOUS_STEPS)
# Statistics
self.stats_activation_count = 0
self.stats_activation_rate = 0.0
self.stats_predition_count = 0
self.stats_precision_rate = 0.0
# 3D object reference
self.tree3d_initialized = False
self.tree3d_start_pos = (0, 0, 0)
self.tree3d_end_pos = (0, 0, 0)
self.tree3d_item_np = None
self.tree3d_selected = False
def initialize(self):
"""
Initialize this node.
"""
# Create Classifier instance with appropriate parameters
self.minProbabilityThreshold = 0.0001
self.steps = []
for step in range(maxFutureSteps):
self.steps.append(step + 1)
self.classifier = CLAClassifier(steps=self.steps)
# Increase history according to inference flag
if self.enableInference:
maxLen = maxPreviousStepsWithInference
self.bestPredictedValue = MachineState(0, maxLen)
else:
maxLen = maxPreviousSteps
self.currentValue = MachineState(0, maxLen)
def __init__(self):
"""
Initializes a new instance of this class.
"""
#region Instance fields
self.dataSourceFieldName = ''
"""Target field of the database table or file."""
self.dataSourceFieldDataType = FieldDataType.string
"""Data type of the field returned by database table or file."""
self.encoder = None
"""Optional encoder to convert raw data to htm input and vice-versa."""
self.encoderModule = ""
"""Module name which encoder class is imported."""
self.encoderClass = ""
"""Class name which encode or decode values."""
self.encoderParams = ""
"""Parameters passed to the encoder class constructor."""
self.encoderFieldName = ""
"""Field name returned by encoder when decode() function."""
self.encoderFieldDataType = FieldDataType.string
"""Data type of the field returned by encoder."""
self.enableInference = False
"""Enable inference for this field."""
self.currentValue = MachineState(None, maxPreviousSteps)
"""Value read currently from database."""
self.bestPredictedValue = MachineState(None, maxPreviousSteps)
"""Best value predicted by network. This is need to build predictions chart."""
self.predictedValues = MachineState(None, maxPreviousSteps)
"""Values predicted by network."""
def initialize(self):
"""
Initialize this bit.
"""
self.x = -1
"""Position on X axis"""
self.y = -1
"""Position on Y axis"""
# States of this element
self.isActive = MachineState(False, maxPreviousSteps)
self.isPredicted = MachineState(False, maxPreviousSteps)
self.isFalselyPredicted = MachineState(False, maxPreviousSteps)
#region Statistics properties
self.statsActivationCount = 0
self.statsActivationRate = 0.
self.statsPreditionCount = 0
self.statsPrecisionRate = 0.
#endregion
#region 3d-tree properties (simulation form)
self.tree3d_initialized = False
self.tree3d_x = 0
self.tree3d_y = 0
self.tree3d_z = 0
self.tree3d_item = None
self.tree3d_selected = False
def initialize(self):
"""
Initialize this bit.
"""
# Position on X axis
self.x = -1
# Position on Y axis
self.y = -1
# States of this element
self.is_active = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_predicted = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_falsely_predicted = MachineState(False, MAX_PREVIOUS_STEPS)
# Statistics
self.stats_activation_count = 0
self.stats_activation_rate = 0.0
self.stats_predition_count = 0
self.stats_precision_rate = 0.0
# 3D object reference
self.tree3d_initialized = False
self.tree3d_pos = (0, 0, 0)
self.tree3d_item_np = None
self.tree3d_selected = False
def __init__(self):
"""
Initializes a new instance of this class.
"""
#region Instance fields
self.indexSP = -1
"""Index of this cell in the spatial pooler."""
self.indexTP = -1
"""Index of this synapse in the temporal pooler."""
self.inputElem = None
"""An input element is a cell in case of the source be a column or then a bit in case of the source be a sensor"""
self.permanence = MachineState(0., maxPreviousSteps)
"""Permanence of this synapse."""
# States of this element
self.isConnected = MachineState(False, maxPreviousSteps)
self.isPredicted = MachineState(False, maxPreviousSteps)
self.isFalselyPredicted = MachineState(False, maxPreviousSteps)
self.isRemoved = MachineState(False, maxPreviousSteps)
#region Statistics properties
self.statsConnectionCount = 0
self.statsConnectionRate = 0.
self.statsPreditionCount = 0
self.statsPrecisionRate = 0.
#endregion
#region 3d-tree properties (simulation form)
self.tree3d_initialized = False
self.tree3d_item = None
self.tree3d_selected = False
def __init__(self):
"""
Initializes a new instance of this class.
"""
#region Instance fields
self.indexSP = -1
"""Index of this cell in the spatial pooler."""
self.indexTP = -1
"""Index of this synapse in the temporal pooler."""
self.inputElem = None
"""An input element is a cell in case of the source be a column or then a bit in case of the source be a sensor"""
self.permanence = MachineState(0., maxPreviousSteps)
"""Permanence of this synapse."""
# States of this element
self.isConnected = MachineState(False, maxPreviousSteps)
self.isPredicted = MachineState(False, maxPreviousSteps)
self.isFalselyPredicted = MachineState(False, maxPreviousSteps)
self.isRemoved = MachineState(False, maxPreviousSteps)
#region Statistics properties
self.statsConnectionCount = 0
self.statsConnectionRate = 0.
self.statsPreditionCount = 0
self.statsPrecisionRate = 0.
#endregion
#region 3d-tree properties (simulation form)
self.tree3d_initialized = False
self.tree3d_item = None
self.tree3d_selected = False
def __init__(self):
"""
Initializes a new instance of this class.
"""
#region Instance fields
self.index = -1
"""Index of this cell in the temporal pooler."""
self.z = -1
"""Position on Z axis"""
self.segments = []
"""List of distal segments of this cell."""
# States of this element
self.isLearning = MachineState(False, maxPreviousSteps)
self.isActive = MachineState(False, maxPreviousSteps)
self.isPredicted = MachineState(False, maxPreviousSteps)
self.isFalselyPredicted = MachineState(False, maxPreviousSteps)
#region Statistics properties
self.statsActivationCount = 0
self.statsActivationRate = 0.
self.statsPreditionCount = 0
self.statsPrecisionRate = 0.
#endregion
#region 3d-tree properties (simulation form)
self.tree3d_initialized = False
self.tree3d_x = 0
self.tree3d_y = 0
self.tree3d_z = 0
self.tree3d_item = None
self.tree3d_selected = False
def buttonInit_click(self, event):
"""
Initializes the HTM-Network by creating the htm-controller to connect to events database
"""
# Initialize the network starting from top region.
start_time = time.time()
end_time = time.time()
initialized = Global.project.network.initialize()
if initialized:
self.state = State.SIMULATING
# Create a simulation
#TODO: self.simulation = Simulation(self.project, self.getProjectPath())
self.simulation = Simulation(None, None)
# Initialize time steps parameters
Global.curr_step = 0
Global.sel_step = 0
Global.time_steps_predictions_chart = MachineState(
0, MAX_PREVIOUS_STEPS_WITH_INFERENCE)
self.output_window.addText("Initialization: " +
"{0:.3f}".format(end_time -
start_time) + " secs")
self.output_window.addText("")
self.output_window.addText("Step\tTime (secs)\tAccuracy (%)")
# Perfoms actions related to time step progression.
start_time = time.time()
Global.project.network.nextStep()
Global.project.network.calculateStatistics()
end_time = time.time()
self.output_window.addText(
str(Global.curr_step + 1) +
"\t{0:.3f}".format(end_time - start_time) +
"\t{0:.3f}".format(Global.project.network.stats_precision_rate)
)
# Disable relevant buttons:
self.enableSteeringButtons(True)
self.enableSimulationButtons(True)
# Update controls
self.simulation_window.viewer_3d.initializeControls(
Global.project.network.nodes[0])
self.refreshControls()
self.update_timer.setInterval(1)
self.update_timer.start()
def __init__(self, type):
"""
Initializes a new instance of this class.
"""
#region Instance fields
self.type = type
"""Determine if this segment is proximal or distal."""
self.indexTP = -1
"""Index of this segment in the temporal pooler."""
self.synapses = []
"""List of distal synapses of this segment."""
# States of this element
self.isActive = MachineState(False, maxPreviousSteps)
self.isPredicted = MachineState(False, maxPreviousSteps)
self.isFalselyPredicted = MachineState(False, maxPreviousSteps)
self.isRemoved = MachineState(False, maxPreviousSteps)
#region Statistics properties
self.statsActivationCount = 0
self.statsActivationRate = 0.
self.statsPreditionCount = 0
self.statsPrecisionRate = 0.
#endregion
#region 3d-tree properties (simulation form)
self.tree3d_initialized = False
self.tree3d_x1 = 0
self.tree3d_y1 = 0
self.tree3d_z1 = 0
self.tree3d_x2 = 0
self.tree3d_y2 = 0
self.tree3d_z2 = 0
self.tree3d_item = None
self.tree3d_selected = False
def __buttonInitHTM_Click(self, event):
"""
Initializes the HTM-Network by creating the htm-controller to connect to events database
"""
# Initialize the network starting from top region.
startTime = time.time()
endTime = time.time()
initialized = Global.project.network.initialize()
if initialized:
# Initialize time steps parameters
Global.currStep = 0
Global.selStep = 0
Global.timeStepsPredictionsChart = MachineState(
0, maxPreviousStepsWithInference)
Global.outputForm.addText("Initialization: " +
"{0:.3f}".format(endTime - startTime) +
" secs")
Global.outputForm.addText("")
Global.outputForm.addText("Step\tTime (secs)\tAccuracy (%)")
# Perfoms actions related to time step progression.
startTime = time.time()
Global.project.network.nextStep()
Global.project.network.calculateStatistics()
endTime = time.time()
Global.outputForm.addText(
str(Global.currStep + 1) +
"\t{0:.3f}".format(endTime - startTime) +
"\t{0:.3f}".format(Global.project.network.statsPrecisionRate))
# Disable relevant buttons:
self.__enableSteeringButtons(True)
self.__enableSimulationButtons(True)
# Update controls
Global.simulationForm.topRegion = Global.project.network.nodes[0]
Global.simulationForm.initializeControls()
self.refreshControls()
def __init__(self):
"""
Initializes a new instance of this class.
"""
#region Instance fields
self.index = -1
"""Index of this cell in the temporal pooler."""
self.z = -1
"""Position on Z axis"""
self.segments = []
"""List of distal segments of this cell."""
# States of this element
self.isLearning = MachineState(False, maxPreviousSteps)
self.isActive = MachineState(False, maxPreviousSteps)
self.isPredicted = MachineState(False, maxPreviousSteps)
self.isFalselyPredicted = MachineState(False, maxPreviousSteps)
#region Statistics properties
self.statsActivationCount = 0
self.statsActivationRate = 0.
self.statsPreditionCount = 0
self.statsPrecisionRate = 0.
#endregion
#region 3d-tree properties (simulation form)
self.tree3d_initialized = False
self.tree3d_x = 0
self.tree3d_y = 0
self.tree3d_z = 0
self.tree3d_item = None
self.tree3d_selected = False
class Cell:
"""
A class only to group properties related to cells.
"""
def __init__(self):
"""
Initializes a new instance of this class.
"""
# Index of this cell in the temporal pooler.
self.index = -1
# Position on Z axis
self.z = -1
# List of distal segments of this cell.
self.segments = []
# States of this element
self.is_learning = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_active = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_predicted = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_falsely_predicted = MachineState(False, MAX_PREVIOUS_STEPS)
# Statistics
self.stats_activation_count = 0
self.stats_activation_rate = 0.0
self.stats_predition_count = 0
self.stats_precision_rate = 0.0
# 3D object reference
self.tree3d_initialized = False
self.tree3d_pos = (0, 0, 0)
self.tree3d_item_np = None
self.tree3d_selected = False
def nextStep(self):
"""
Perfoms actions related to time step progression.
"""
# Update states machine by remove the first element and add a new element in the end
self.is_learning.rotate()
self.is_active.rotate()
self.is_predicted.rotate()
self.is_falsely_predicted.rotate()
# Remove segments (and their synapses) that are marked to be removed
for segment in self.segments:
if segment.is_removed.atFirstStep():
for synapse in segment.synapses:
segment.synapses.remove(synapse)
del synapse
self.segments.remove(segment)
del segment
for segment in self.segments:
segment.nextStep()
def calculateStatistics(self):
"""
Calculate statistics after an iteration.
"""
# Calculate statistics
if self.is_active.atCurrStep():
self.stats_activation_count += 1
if self.is_predicted.atCurrStep():
self.stats_predition_count += 1
if Global.curr_step > 0:
self.stats_activation_rate = self.stats_activation_count / float(
Global.curr_step)
if self.stats_activation_count > 0:
self.stats_precision_rate = self.stats_predition_count / float(
self.stats_activation_count)
for segment in self.segments:
segment.calculateStatistics()
class Bit:
"""
A class only to group properties related to input bits of sensors.
"""
def __init__(self):
"""
Initializes a new instance of this class.
"""
self.initialize()
def initialize(self):
"""
Initialize this bit.
"""
# Position on X axis
self.x = -1
# Position on Y axis
self.y = -1
# States of this element
self.is_active = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_predicted = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_falsely_predicted = MachineState(False, MAX_PREVIOUS_STEPS)
# Statistics
self.stats_activation_count = 0
self.stats_activation_rate = 0.0
self.stats_predition_count = 0
self.stats_precision_rate = 0.0
# 3D object reference
self.tree3d_initialized = False
self.tree3d_pos = (0, 0, 0)
self.tree3d_item_np = None
self.tree3d_selected = False
def nextStep(self):
"""
Perfoms actions related to time step progression.
"""
# Update states machine by remove the first element and add a new element in the end
self.is_active.rotate()
self.is_predicted.rotate()
self.is_falsely_predicted.rotate()
def calculateStatistics(self):
"""
Calculate statistics after an iteration.
"""
# Calculate statistics
if self.is_active.atCurrStep():
self.stats_activation_count += 1
if self.is_predicted.atCurrStep():
self.stats_predition_count += 1
if Global.curr_step > 0:
self.stats_activation_rate = self.stats_activation_count / float(
Global.curr_step)
if self.stats_activation_count > 0:
self.stats_precision_rate = self.stats_predition_count / float(
self.stats_activation_count)
class Cell:
"""
A class only to group properties related to cells.
"""
#region Constructor
def __init__(self):
"""
Initializes a new instance of this class.
"""
#region Instance fields
self.index = -1
"""Index of this cell in the temporal pooler."""
self.z = -1
"""Position on Z axis"""
self.segments = []
"""List of distal segments of this cell."""
# States of this element
self.isLearning = MachineState(False, maxPreviousSteps)
self.isActive = MachineState(False, maxPreviousSteps)
self.isPredicted = MachineState(False, maxPreviousSteps)
self.isFalselyPredicted = MachineState(False, maxPreviousSteps)
#region Statistics properties
self.statsActivationCount = 0
self.statsActivationRate = 0.
self.statsPreditionCount = 0
self.statsPrecisionRate = 0.
#endregion
#region 3d-tree properties (simulation form)
self.tree3d_initialized = False
self.tree3d_x = 0
self.tree3d_y = 0
self.tree3d_z = 0
self.tree3d_item = None
self.tree3d_selected = False
#endregion
#endregion
#endregion
#region Methods
def nextStep(self):
"""
Perfoms actions related to time step progression.
"""
# Update states machine by remove the first element and add a new element in the end
self.isLearning.rotate()
self.isActive.rotate()
self.isPredicted.rotate()
self.isFalselyPredicted.rotate()
# Remove segments (and their synapses) that are marked to be removed
for segment in self.segments:
if segment.isRemoved.atFirstStep():
for synapse in segment.synapses:
segment.synapses.remove(synapse)
del synapse
self.segments.remove(segment)
del segment
for segment in self.segments:
segment.nextStep()
def calculateStatistics(self):
"""
Calculate statistics after an iteration.
"""
# Calculate statistics
if self.isActive.atCurrStep():
self.statsActivationCount += 1
if self.isPredicted.atCurrStep():
self.statsPreditionCount += 1
if Global.currStep > 0:
self.statsActivationRate = self.statsActivationCount / float(
Global.currStep)
if self.statsActivationCount > 0:
self.statsPrecisionRate = self.statsPreditionCount / float(
self.statsActivationCount)
for segment in self.segments:
segment.calculateStatistics()
class Synapse:
"""
A class only to group properties related to synapses.
"""
#region Constructor
def __init__(self):
"""
Initializes a new instance of this class.
"""
#region Instance fields
self.indexSP = -1
"""Index of this cell in the spatial pooler."""
self.indexTP = -1
"""Index of this synapse in the temporal pooler."""
self.inputElem = None
"""An input element is a cell in case of the source be a column or then a bit in case of the source be a sensor"""
self.permanence = MachineState(0., maxPreviousSteps)
"""Permanence of this synapse."""
# States of this element
self.isConnected = MachineState(False, maxPreviousSteps)
self.isPredicted = MachineState(False, maxPreviousSteps)
self.isFalselyPredicted = MachineState(False, maxPreviousSteps)
self.isRemoved = MachineState(False, maxPreviousSteps)
#region Statistics properties
self.statsConnectionCount = 0
self.statsConnectionRate = 0.
self.statsPreditionCount = 0
self.statsPrecisionRate = 0.
#endregion
#region 3d-tree properties (simulation form)
self.tree3d_initialized = False
self.tree3d_item = None
self.tree3d_selected = False
#endregion
#endregion
#endregion
#region Methods
def nextStep(self):
"""
Perfoms actions related to time step progression.
"""
# Update states machine by remove the first element and add a new element in the end
self.permanence.rotate()
self.isConnected.rotate()
self.isPredicted.rotate()
self.isFalselyPredicted.rotate()
self.isRemoved.rotate()
def calculateStatistics(self):
"""
Calculate statistics after an iteration.
"""
# Calculate statistics
if self.isConnected.atCurrStep():
self.statsConnectionCount += 1
if self.isPredicted.atCurrStep():
self.statsPreditionCount += 1
if Global.currStep > 0:
self.statsConnectionRate = self.statsConnectionCount / float(Global.currStep)
if self.statsConnectionCount > 0:
self.statsPrecisionRate = self.statsPreditionCount / float(self.statsConnectionCount)
class Bit:
"""
A class only to group properties related to input bits of sensors.
"""
#region Constructor
def __init__(self):
"""
Initializes a new instance of this class.
"""
self.initialize()
#endregion
#region Methods
def initialize(self):
"""
Initialize this bit.
"""
self.x = -1
"""Position on X axis"""
self.y = -1
"""Position on Y axis"""
# States of this element
self.isActive = MachineState(False, maxPreviousSteps)
self.isPredicted = MachineState(False, maxPreviousSteps)
self.isFalselyPredicted = MachineState(False, maxPreviousSteps)
#region Statistics properties
self.statsActivationCount = 0
self.statsActivationRate = 0.
self.statsPreditionCount = 0
self.statsPrecisionRate = 0.
#endregion
#region 3d-tree properties (simulation form)
self.tree3d_initialized = False
self.tree3d_x = 0
self.tree3d_y = 0
self.tree3d_z = 0
self.tree3d_item = None
self.tree3d_selected = False
#endregion
def nextStep(self):
"""
Perfoms actions related to time step progression.
"""
# Update states machine by remove the first element and add a new element in the end
self.isActive.rotate()
self.isPredicted.rotate()
self.isFalselyPredicted.rotate()
def calculateStatistics(self):
"""
Calculate statistics after an iteration.
"""
# Calculate statistics
if self.isActive.atCurrStep():
self.statsActivationCount += 1
if self.isPredicted.atCurrStep():
self.statsPreditionCount += 1
if Global.currStep > 0:
self.statsActivationRate = self.statsActivationCount / float(Global.currStep)
if self.statsActivationCount > 0:
self.statsPrecisionRate = self.statsPreditionCount / float(self.statsActivationCount)
class Synapse:
"""
A class only to group properties related to synapses.
"""
def __init__(self):
"""
Initializes a new instance of this class.
"""
# Index of this cell in the spatial pooler.
self.index_sp = -1
# Index of this synapse in the temporal pooler.
self.index_tp = -1
# An input element is a cell in case of the source be a column or then a bit in case of the source be a sensor.
self.input_elem = None
# Permanence of this synapse.
self.permanence = MachineState(0.0, MAX_PREVIOUS_STEPS)
# States of this element
self.is_connected = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_predicted = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_falsely_predicted = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_removed = MachineState(False, MAX_PREVIOUS_STEPS)
# Statistics
self.stats_connection_count = 0
self.stats_connection_rate = 0.0
self.stats_predition_count = 0
self.stats_precision_rate = 0.0
# 3D object reference
self.tree3d_initialized = False
self.tree3d_item_np = None
self.tree3d_selected = False
def nextStep(self):
"""
Perfoms actions related to time step progression.
"""
# Update states machine by remove the first element and add a new element in the end
self.permanence.rotate()
self.is_connected.rotate()
self.is_predicted.rotate()
self.is_falsely_predicted.rotate()
self.is_removed.rotate()
def calculateStatistics(self):
"""
Calculate statistics after an iteration.
"""
# Calculate statistics
if self.is_connected.atCurrStep():
self.stats_connection_count += 1
if self.is_predicted.atCurrStep():
self.stats_predition_count += 1
if Global.curr_step > 0:
self.stats_connection_rate = self.stats_connection_count / float(
Global.curr_step)
if self.stats_connection_count > 0:
self.stats_precision_rate = self.stats_predition_count / float(
self.stats_connection_count)
class Cell:
"""
A class only to group properties related to cells.
"""
#region Constructor
def __init__(self):
"""
Initializes a new instance of this class.
"""
#region Instance fields
self.index = -1
"""Index of this cell in the temporal pooler."""
self.z = -1
"""Position on Z axis"""
self.segments = []
"""List of distal segments of this cell."""
# States of this element
self.isLearning = MachineState(False, maxPreviousSteps)
self.isActive = MachineState(False, maxPreviousSteps)
self.isPredicted = MachineState(False, maxPreviousSteps)
self.isFalselyPredicted = MachineState(False, maxPreviousSteps)
#region Statistics properties
self.statsActivationCount = 0
self.statsActivationRate = 0.
self.statsPreditionCount = 0
self.statsPrecisionRate = 0.
#endregion
#region 3d-tree properties (simulation form)
self.tree3d_initialized = False
self.tree3d_x = 0
self.tree3d_y = 0
self.tree3d_z = 0
self.tree3d_item = None
self.tree3d_selected = False
#endregion
#endregion
#endregion
#region Methods
def nextStep(self):
"""
Perfoms actions related to time step progression.
"""
# Update states machine by remove the first element and add a new element in the end
self.isLearning.rotate()
self.isActive.rotate()
self.isPredicted.rotate()
self.isFalselyPredicted.rotate()
# Remove segments (and their synapses) that are marked to be removed
for segment in self.segments:
if segment.isRemoved.atFirstStep():
for synapse in segment.synapses:
segment.synapses.remove(synapse)
del synapse
self.segments.remove(segment)
del segment
for segment in self.segments:
segment.nextStep()
def calculateStatistics(self):
"""
Calculate statistics after an iteration.
"""
# Calculate statistics
if self.isActive.atCurrStep():
self.statsActivationCount += 1
if self.isPredicted.atCurrStep():
self.statsPreditionCount += 1
if Global.currStep > 0:
self.statsActivationRate = self.statsActivationCount / float(Global.currStep)
if self.statsActivationCount > 0:
self.statsPrecisionRate = self.statsPreditionCount / float(self.statsActivationCount)
for segment in self.segments:
segment.calculateStatistics()
class Segment:
"""
A class only to group properties related to segments.
"""
#region Constructor
def __init__(self, type):
"""
Initializes a new instance of this class.
"""
#region Instance fields
self.type = type
"""Determine if this segment is proximal or distal."""
self.indexTP = -1
"""Index of this segment in the temporal pooler."""
self.synapses = []
"""List of distal synapses of this segment."""
# States of this element
self.isActive = MachineState(False, maxPreviousSteps)
self.isPredicted = MachineState(False, maxPreviousSteps)
self.isFalselyPredicted = MachineState(False, maxPreviousSteps)
self.isRemoved = MachineState(False, maxPreviousSteps)
#region Statistics properties
self.statsActivationCount = 0
self.statsActivationRate = 0.
self.statsPreditionCount = 0
self.statsPrecisionRate = 0.
#endregion
#region 3d-tree properties (simulation form)
self.tree3d_initialized = False
self.tree3d_x1 = 0
self.tree3d_y1 = 0
self.tree3d_z1 = 0
self.tree3d_x2 = 0
self.tree3d_y2 = 0
self.tree3d_z2 = 0
self.tree3d_item = None
self.tree3d_selected = False
#endregion
#endregion
#endregion
#region Methods
def getSynapse(self, indexSP):
"""
Return the synapse connected to a given cell or sensor bit
"""
synapse = None
for synapse in self.synapses:
if synapse.indexSP == indexSP:
return synapse
def nextStep(self):
"""
Perfoms actions related to time step progression.
"""
# Update states machine by remove the first element and add a new element in the end
self.isActive.rotate()
self.isPredicted.rotate()
self.isFalselyPredicted.rotate()
self.isRemoved.rotate()
# Remove synapses that are marked to be removed
for synapse in self.synapses:
if synapse.isRemoved.atFirstStep():
self.synapses.remove(synapse)
del synapse
for synapse in self.synapses:
synapse.nextStep()
def calculateStatistics(self):
"""
Calculate statistics after an iteration.
"""
# Calculate statistics
if self.isActive.atCurrStep():
self.statsActivationCount += 1
if self.isPredicted.atCurrStep():
self.statsPreditionCount += 1
if Global.currStep > 0:
self.statsActivationRate = self.statsActivationCount / float(Global.currStep)
if self.statsActivationCount > 0:
self.statsPrecisionRate = self.statsPreditionCount / float(self.statsActivationCount)
for synapse in self.synapses:
synapse.calculateStatistics()
class Synapse:
"""
A class only to group properties related to synapses.
"""
#region Constructor
def __init__(self):
"""
Initializes a new instance of this class.
"""
#region Instance fields
self.indexSP = -1
"""Index of this cell in the spatial pooler."""
self.indexTP = -1
"""Index of this synapse in the temporal pooler."""
self.inputElem = None
"""An input element is a cell in case of the source be a column or then a bit in case of the source be a sensor"""
self.permanence = MachineState(0., maxPreviousSteps)
"""Permanence of this synapse."""
# States of this element
self.isConnected = MachineState(False, maxPreviousSteps)
self.isPredicted = MachineState(False, maxPreviousSteps)
self.isFalselyPredicted = MachineState(False, maxPreviousSteps)
self.isRemoved = MachineState(False, maxPreviousSteps)
#region Statistics properties
self.statsConnectionCount = 0
self.statsConnectionRate = 0.
self.statsPreditionCount = 0
self.statsPrecisionRate = 0.
#endregion
#region 3d-tree properties (simulation form)
self.tree3d_initialized = False
self.tree3d_item = None
self.tree3d_selected = False
#endregion
#endregion
#endregion
#region Methods
def nextStep(self):
"""
Perfoms actions related to time step progression.
"""
# Update states machine by remove the first element and add a new element in the end
self.permanence.rotate()
self.isConnected.rotate()
self.isPredicted.rotate()
self.isFalselyPredicted.rotate()
self.isRemoved.rotate()
def calculateStatistics(self):
"""
Calculate statistics after an iteration.
"""
# Calculate statistics
if self.isConnected.atCurrStep():
self.statsConnectionCount += 1
if self.isPredicted.atCurrStep():
self.statsPreditionCount += 1
if Global.currStep > 0:
self.statsConnectionRate = self.statsConnectionCount / float(
Global.currStep)
if self.statsConnectionCount > 0:
self.statsPrecisionRate = self.statsPreditionCount / float(
self.statsConnectionCount)
class Segment:
"""
A class only to group properties related to segments.
"""
def __init__(self, type):
"""
Initializes a new instance of this class.
"""
# Determine if this segment is proximal or distal.
self.type = type
# Index of this segment in the temporal pooler.
self.index_tp = -1
# List of distal synapses of this segment.
self.synapses = []
# States of this element
self.is_active = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_predicted = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_falsely_predicted = MachineState(False, MAX_PREVIOUS_STEPS)
self.is_removed = MachineState(False, MAX_PREVIOUS_STEPS)
# Statistics
self.stats_activation_count = 0
self.stats_activation_rate = 0.0
self.stats_predition_count = 0
self.stats_precision_rate = 0.0
# 3D object reference
self.tree3d_initialized = False
self.tree3d_start_pos = (0, 0, 0)
self.tree3d_end_pos = (0, 0, 0)
self.tree3d_item_np = None
self.tree3d_selected = False
def getSynapse(self, index_sp):
"""
Return the synapse connected to a given cell or sensor bit
"""
for synapse in self.synapses:
if synapse.index_sp == index_sp:
return synapse
return None
def nextStep(self):
"""
Perfoms actions related to time step progression.
"""
# Update states machine by remove the first element and add a new element in the end
self.is_active.rotate()
self.is_predicted.rotate()
self.is_falsely_predicted.rotate()
self.is_removed.rotate()
# Remove synapses that are marked to be removed
for synapse in self.synapses:
if synapse.is_removed.atFirstStep():
self.synapses.remove(synapse)
del synapse
for synapse in self.synapses:
synapse.nextStep()
def calculateStatistics(self):
"""
Calculate statistics after an iteration.
"""
# Calculate statistics
if self.is_active.atCurrStep():
self.stats_activation_count += 1
if self.is_predicted.atCurrStep():
self.stats_predition_count += 1
if Global.curr_step > 0:
self.stats_activation_rate = self.stats_activation_count / float(
Global.curr_step)
if self.stats_activation_count > 0:
self.stats_precision_rate = self.stats_predition_count / float(
self.stats_activation_count)
for synapse in self.synapses:
synapse.calculateStatistics()
